Research and application of tongue and face diagnosis based on deep learning.

Objective: To explore the technical research and application characteristics of deep learning in tongue-facial diagnosis. Methods: Through summarizing the merits and demerits of current image processing techniques used in the traditional medical tongue and face diagnosis, the research status of deep learning in tongue image preprocessing, segmentation, and classification was analyzed and reviewed, and the algorithm was compared and verified with the real tongue and face image. Images of the face and tongue used for diagnosis in conventional medicine were systematically reviewed, from acquisition and pre-processing to segmentation, classification, algorithm comparison, result from analysis, and application. Results: Deep learning improved the speed and accuracy of tongue and face diagnostic image data processing. Among them, the average intersection ratio of U-net and Seg-net models exceeded 0.98, and the segmentation speed ranged from 54 to 58 ms. Conclusion: There is no unified standard for lingual-facial diagnosis objectification in terms of image acquisition conditions and image processing methods, thus further research is indispensable. It is feasible to use the images acquired by mobile in the field of medical image analysis by reducing the influence of environmental and other factors on the quality of lingual-facial diagnosis images and improving the efficiency of image processing.

A coordinate-based meta-analysis of acupuncture for chronic pain: Evidence from fMRI studies.

Background: Chronic pain (CP) patients tend to represent aberrant functional brain activity. Acupuncture is an effective clinical treatment for CP, and some fMRI studies were conducted to discover the alternation of brain regions after acupuncture therapy for CP. However, the heterogeneity of neuroimaging studies has prevented researchers from systematically generalizing the central mechanisms of acupuncture in the treatment of CP. Methods: We searched bibliographic databases, including PubMed, EMBASE, PsycINFO, Web of Science Core Collection, ScienceDirect, China Academic Journal Network Publishing Database, etc., and trials registration platforms (From inception to September 1st, 2022). Two independent researchers assessed the study's bias and quality. Furthermore, activation likelihood estimation (ALE) analysis was applied to explore aberrant brain functional activity and acupuncture's central mechanism for CP. Results: Totally 14 studies with 524 CP patients were included in the study. ALE analysis showed that CP patients presented with decreased ALFF/ReHo in the precuneus, posterior cingulate cortex, right inferior parietal lobule, right superior temporal gyrus, cingulate gyrus, superior frontal gyrus, left medial frontal gyrus including medial prefrontal gurus, left middle frontal gyrus. Conclusion: This ALE meta-analysis pointed out that acupuncture could modulate the default mode network, the frontoparietal network to treat CP. This provided a systematic summary of the neuroimage biomarker of acupuncture for the treatment of CP. Systematic review registration: PROSPERO, identifier: CRD42021239633.

Traditional Chinese Medicine Aconiti Radix Cocta Improves Rheumatoid Arthritis via Suppressing COX-1 and COX-2.

According to Traditional Chinese Medicine (TCM), Aconiti Radix Cocta (AC) is clinically employed to expel wind, remove dampness, and relieve pain. We evaluated the antirheumatoid arthritis (RA) activities and underlying mechanisms of AC. The chemical constituents of AC were analyzed by high-performance liquid chromatography (HPLC) using three reference compounds (benzoylaconitine, benzoylmesaconine, and benzoylhypacoitine). The anti-RA effects of AC were evaluated in adjuvant-induced arthritis (AIA) rats by hind paw volume and histopathological analysis. The effects of AC on inflammatory cytokines (IL-1ß and IL-17A) were determined by enzyme-linked immunosorbent assay. The regulation of cyclooxygenases (COX-1 and/or COX-2) was determined by Western blot and real-time quantitative reverse transcription polymerase chain reaction analyses. AC significantly reduced paw swelling, attenuated the inflammation and bone destruction in joint tissues, and reduced IL-1ß and IL-17A in the serum. Moreover, AC downregulated the expression of COX-1 and COX-2 in the synovial tissues. We also identified that AC possesses significant anti-RA activities on AIA, which may be ascribed to the regulation of inflammatory cytokines IL-1ß and IL-17, as well as to the inhibition of arachidonic acid signaling pathways. Our findings provide theoretical support for AC as an effective nature-derived therapeutic agent for RA treatment.

Network differentiation: A computational method of pathogenesis diagnosis in traditional Chinese medicine based on systems science.

Resembling the role of disease diagnosis in Western medicine, pathogenesis (also called Bing Ji) diagnosis is one of the utmost important tasks in traditional Chinese medicine (TCM). In TCM theory, pathogenesis is a complex system composed of a group of interrelated factors, which is highly consistent with the character of systems science (SS). In this paper, we introduce a heuristic definition called pathogenesis network (PN) to represent pathogenesis in the form of the directed graph. Accordingly, a computational method of pathogenesis diagnosis, called network differentiation (ND), is proposed by integrating the holism principle in SS. ND consists of three stages. The first stage is to generate all possible diagnoses by Cartesian Product operated on specified prior knowledge corresponding to the input symptoms. The second stage is to screen the validated diagnoses by holism principle. The third stage is to pick out the clinical diagnosis by physician-computer interaction. Some theorems are stated and proved for the further optimization of ND in this paper. We conducted simulation experiments on 100 clinical cases. The experimental results show that our proposed method has an excellent capability to fit the holistic thinking in the process of physician inference.

Research on Standard Compliance Test Algorithm Based on Electronic Medical Records of Traditional Chinese Medicine Outpatients.

Objectives: To effectively evaluate the compliance degree between the electronic medical records of Traditional Chinese Medicine (TCM) hospitals, as well as the information platform, and the related information standards of electronic medical records, a standard compliance testing scheme based on electronic medical records of TCM outpatients is proposed. Methods: This research selected the data of clinical outpatients accumulated in 10 years by the Digital Medicine Institute of Chengdu University of TCM and processed the data through security check and desensitization process. And then 28348 cases of processed electronic medical records of TCM outpatients were inputted into the standard compliance testing platform for assessment. The result was then outputted. Results: There are 924 cases among the 28348 that can be rated as five-star medical records, 84 cases four-star, 132 cases three-star, 12460 cases two-star, 13488 one-star, and 1260 cases zero-star through the integrity and standardization test. Conclusion: By the way of assessing the integrity and standardization of data, the standard compliance test algorithm scheme for electronic medical records of TCM outpatients introduced in this paper can solve the problems such as data unavailability caused by ununified codes and incomplete data in the data-sharing process and provides technical support for the construction of data standardization testing in electronic medical records of TCM outpatients.

[Chemical components and pharmacological action of Aconiti Radix].

Aconiti Radix is a commonly used traditional Chinese medicine( TCM) herb in clinic,with the effects in expelling wind and removing damness,warming menstruation and relieving pain. With a long medicinal history and high medicinal value,it was used for anemofrigid-damp arthralgia,arthralgia,cold hernia and anesthesia analgesia. Modern pharmacological studies have shown that Aconiti Radix has a good therapeutic effect on rheumatoid arthritis,neuropathic pain and hypertension. As a well-known toxic TCM herb,its main pharmacodynamic and toxic components are alkaloids,which can lead to neurotoxicity and cardiotoxicity while exerting anti-inflammatory,analgesic,anti-tumor and other pharmacodynamic effects. Therefore,it is often processed to reduce its toxicity or combined with Paeoniae Radix Alba and Stephaniae Tetrandrae Radix to achieve the purpose of reducing toxicity and increasing efficacy in clinic.In recent years,with the deepening of the study on the incompatibility of TCM represented by " eighteen incompatible herbs",there have been new findings about TCM incompatibility. It has been found complementary effect,rather than no obvious toxic and side effects after the combination with incompatible herbs of Aconiti Radix. To provide the basis for further study and clinical application of Aconiti Radix,this paper reviewed chemical components,pharmacological action,toxicity and compatibility of Aconiti Radix by consulting relevant literatures published in recent years at home and abroad. Meanwhile,this paper also described the relationship between chemical constituents,as well as anti-inflammatory,analgesic,anti-tumor and other pharmacological effects and toxicity.

[Anti-inflammatory mechanism analysis of antirheumatic Chinese medicinal herb Aconiti Radix based on protein interaction network].

Inflammation is one of the important risk factors of rheumatic diseases. Aconiti Radix is widely used for the treatment of rheumatism, which has significant anti-inflammatory effects. However, its anti-inflammatory mechanism on molecular level is still not clear. The purpose of this study is to illuminate the anti-inflammatory mechanism of Aconiti Radix based on the protein interaction network (PIN) analysis on molecular network level. The main anti-inflammatory components (aconitine, hypaconitine and mesaconitine) were chosen in this study to obtain the targets of the components and protein-protein information though databases retrieval and construct the PIN of Aconiti Radix. By a graph theoretic clustering algorithm molecular complex detection(MCODE), 13 modules were identified and analyzed by gene ontology(GO) enrichment. The results showed that the anti-inflammatory mechanism of Aconiti Radix was mainly associated with prostanoid metabolic process and leukocyte chemotaxis mediated by chemokines. In this study, the anti-inflammatory mechanism of Aconiti Radix was elucidated systematically from molecular network level, which provided the scientific basis for the treatment of rheumatic diseases.